high performance computing systemsdshook/cse566/lectures/intro.pdfhigh performance computing systems...

High Performance Computing Systems

Course structure and expectationsOverview

Doug Shook via Roger Chamberlain

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Instructor Doug Shook– Office: Jolley 534– Office Hours: Wednesdays 2:30-4

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Course Breakdown Website – www.cse.wustl.edu/~dshook/cse566

Homework – 80%– 4 over the course of the semester– Groups of 2– C/C++

Presentation – 20%– Must submit a proposal by 7/5

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Homework Moderate amounts of programming

More interested in answering (and asking!) questions:– How can we make this code run more efficiently?– What effects do different programming paradigms

have?– How can we measure code performance?

Experiment!

Report

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Policies Grading will be done on a straight scale– Curved if necessary (hint: it probably won't be)

Class attendance is not mandatory

Late work / Extensions

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Academic Dishonesty Collaboration is encouraged!

Over the line– Working in groups of more than 3– Showing your work to another group– Internet usage:• Finding sources, ideas, examples – OK• Copying text, ideas, code – Not OK

Zero Tolerance

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Why do we need HPC? Classic Example: Weather forecasting

– Hundreds of thousands of weather stations, all collecting large amounts of data

– Cubic Grid

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Weather Modeling Assuming that each grid point requires 100 floating point

instructions to process:– How many instructions for one point in time?– Hourly for 2 days?

What would that look like on a...– Pentium 4 (2000)?– Core i7 (2012)?– NCAR Weather Supercomputer?

And that's not even the entire planet....

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Grand Challenges Computing goals set in the late 80s by the government:– Fluid dynamics– Nature of matter– Symbolic computations– Evolution of galaxies– Blood flow through a heart

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Modern Examples IBM Sequoia – 3rd fastest super computer– Used for nuclear weapons simulations• How to dispose of old weapons?

WATSON– Jeopardy!– Human computer interaction

Pleiades– Owned and operated by NASA– Spaceflight simulations– Galaxy collisions

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HPC at Wash U Streaming computing– Autopipe – Dr. Chamberlain

Clusters– We're sitting in one

Med School– Supercomputer with 1800 cores, 19 TFLOPS

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Goals Parallel programs exist, but don't always perform well... – Why?– How can they be improved?– How can we reliably measure performance?

Programming Paradigms– Shared Memory, Message Passing, Streaming– How does the choice of a paradigm affect performance?

Application– What can we learn from existing HPC systems?– What problems exist with current methods?– What can we expect from future systems?

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Tools Profilers– gprof– top– operf– perf

Libraries / Frameworks– BLAS– OpenMP– MPI

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Tools Languages– C/C++– FORTRAN– CUDA / OpenCL– VHDL/Verilog

Platforms– CPU– GPU– FPGA– Hybrid

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